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. 2010 Apr;37(4):313-23.
doi: 10.1111/j.1600-051X.2010.01534.x.

Relationships between subgingival microbiota and GCF biomarkers in generalized aggressive periodontitis

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Relationships between subgingival microbiota and GCF biomarkers in generalized aggressive periodontitis

Ricardo P Teles et al. J Clin Periodontol. 2010 Apr.

Abstract

Aim: To examine relationships between subgingival biofilm composition and levels of gingival crevicular fluid (GCF) cytokines in periodontal health and generalized aggressive periodontitis (GAP).

Materials and methods: Periodontal parameters were measured in 25 periodontally healthy and 31 GAP subjects. Subgingival plaque and GCF samples were obtained from 14 sites from each subject. Forty subgingival taxa were quantified using checkerboard DNA-DNA hybridization and the concentrations of eight GCF cytokines were measured using Luminex. Cluster analysis was used to define sites with similar subgingival microbiotas in each clinical group. Significance of differences in clinical, microbiological and immunological parameters among clusters was determined using the Kruskal-Wallis test.

Results: GAP subjects had statistically significantly higher GCF levels of interleukin-1beta (IL-1beta) (p<0.001), granulocyte-macrophage colony-stimulating factor (GM-CSF) (p<0.01) and IL-1beta/IL-10 ratio (p<0.001) and higher proportions of Red and Orange complex species than periodontally healthy subjects. There were no statistically significant differences in the mean proportion of cytokines among clusters in the periodontally healthy subjects, while the ratio IL-1beta/IL-10 (p<0.05) differed significantly among clusters in the aggressive periodontitis group.

Conclusions: Different subgingival biofilm profiles are associated with distinct patterns of GCF cytokine expression. Aggressive periodontitis subjects were characterized by a higher IL-1beta/IL-10 ratio than periodontally healthy subjects, suggesting an imbalance between pro- and anti-inflammatory cytokines in aggressive periodontitis.

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Figures

Fig. 1
Fig. 1
Mean percentage of the total DNA probe count of the 40 test species in subgingival biofilm samples from up to 14 periodontal sites from each periodontally healthy and generalized aggressive periodontitis subject. Mean % DNA probe count of each species was computed at each site, averaged for each subject, and then averaged across subjects in each group separately. Significance of differences for each species between clinical groups was sought using the Mann Whitney test; * p < 0.05, ** p < 0.01, *** p < 0.001 and adjusted for 40 comparisons (Socransky et al. 1991). The species were ordered and grouped according to the complexes described by Socransky et al. (1998).
Fig. 2
Fig. 2
Grid-plots of the Spearman rank correlation coefficients among the mean proportions of 8 cytokines and the mean proportions of 40 subgingival microbial species for periodontally healthy (left panel) and generalized aggressive periodontitis subjects (right panel). Mean % DNA probe count of each species and the proportion of each cytokine were computed by averaging the data within each subject, and then averaging across subjects in each group separately. The color code indicates the level of the Spearman rank coefficient. Asterisks indicate significance at p < 0.05.
Fig. 3
Fig. 3
Dendrograms of cluster analyses of mean microbial counts of 40 subgingival species in subgingival plaque samples from 330 sites from 21 periodontally healthy subjects (left panel) and 221 sites from 31 generalized aggressive periodontitis subjects (right panel). The counts of 40 bacterial species were determined at each of up o 14 sites in each subject. The counts of the 40 taxa were employed in cluster analyses using the chord coefficient and an average unweighted linkage sort. The colored triangles within each dendrogram indicate the 5 clusters of sites that were formed at > 53% similarity for the periodontally healthy group and at > 33% similarity for the aggressive periodontitis group.
Fig. 4
Fig. 4
Mean counts x 105 of subgingival taxa in the clusters and not-in-cluster group (NIC) detected in 25 periodontally healthy subjects. The counts of 40 subgingival species were measured at each of up to 14 sites in each subject and employed in a cluster analysis using the chord coefficient and an average unweighted linkage sort. Five clusters were formed at > 53% similarity. Nineteen subjects presented at least one site with a microbial profile that did not fit any cluster. After the clusters were identified, data were averaged within a subject and then averaged across subjects in each cluster group separately. The numbers above each panel represent the number of subjects with at least one site with the microbial profile that defined that cluster. The numbers in parentheses represent the total number of sites in each cluster. The pie diagrams indicate the mean proportion of each cytokine in the 5 cluster groups and in the NIC subjects. Significance of differences for each species among cluster groups was sought using the Kruskal-Wallis test; * p < 0.05, ** p < 0.01, *** p < 0.001 and adjusted for 40 comparisons.(Socransky et al. 1991) The species were ordered and grouped according to the complexes described by Socransky et al. (1998).(Socransky et al. 1998) Significance of differences for the proportion of each cytokine among clusters was also examined using the Kruskal-Wallis test.
Fig. 5
Fig. 5
Mean counts x 105 of subgingival taxa in the clusters and not-in-cluster group (NIC) detected in 31 generalized aggressive periodontitis subjects. The counts of 40 subgingival species were measured at each of up to 14 sites in each subject and employed in a cluster analysis using the chord coefficient and an average unweighted linkage sort. Five clusters were formed at > 33% similarity. Four subjects presented at least one site with a microbial profile that did not fit any cluster. The numbers above each panel represent the number of subjects with at least one site with the microbial profile that defined that cluster. The numbers in parentheses represent the total number of sites in each cluster. The pie charts and the statistical analyses were as described for Fig. 4.

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